Imaging of light scattering tissues with fluorescent contrast agents

ABSTRACT

A system and method for non-invasive biomedical optical imaging and spectroscopy with low-level light is described. The technique includes a modulated light source coupled to tissue to introduce excitation light. Fluorescent light emitted in response to the excitation light is detected with a sensor. The AC intensity and phase of the excitation and detected fluorescent light is provided to a processor operatively coupled to the sensor. A processor employs the measured emission kinetics of excitation and fluorescent light to “map” the spatial variation of one or more fluorescence characteristics of the tissue and generate a corresponding image of the tissue via an output device. The fluorescence characteristic may be provided by exogenous contrast agents, endogenous fluorophores, or both. A technique to select or design an exogenous fluorescent contrast agent to improve image contrast is also disclosed.

BACKGROUND OF THE INVENTION

The present invention relates to spectroscopic imaging of heterogeneouslight scattering tissue, and more particularly, but not exclusively,relates to in vivo imaging by mapping a fluorescence characteristic ofthe tissue.

The early detection of disease promises a greater efficacy fortherapeutic intervention. In recent years, noninvasive techniques havebeen developed which have improved the ability to provide a reliable andearly diagnosis of various afflictions by detecting biochemical changesin the tissue of a patient. For example, Magnetic Resonance Imaging(MRI) has successfully monitored the relaxation of spin states ofparamagnetic nuclei in order to provide biomedical imaging andbiochemical spectroscopy of tissues. Unfortunately, the complexity andexpense of MRI diagnostics limit its availability—especially as a meansof routine monitoring for disease.

Another powerful analytical technique with an increasing number ofapplications in the biological sciences is fluorescence spectroscopy.Applications of fluorescence spectroscopy include biomedicaldiagnostics, genetic sequencing, and flow cytometry. As exemplified byU.S. Pat. Nos. 5,421,337 to Richards-Kortum et al. and 5,452,723 to Wuet al., several investigators have suggested various procedures todifferentiate diseased and normal tissues based on fluorescenceemissions through noninvasive external measurements or minimallyinvasive endoscopic measuring techniques. Unfortunately, theseprocedures generally fail to provide a viable spatial imaging procedure.One reason imaging based on fluorescence has remained elusive is thatmeaningful relational measurements of fluorescence characteristics froma random, multiply scattering media, such as tissue, are difficult toobtain. For example, fluorescent intensity, which is a function of thefluorescent compound (or fluorophore) concentration or “uptake” is onepossible candidate for imaging; however, when this property is used inan optically dense medium, such as a particulate (cell) suspension,powder, or tissue, the local scattering and absorption propertiesconfound measured fluorescent intensities.

Besides intensity, other properties of selected fluorophores such asfluorescent quantum efficiency and lifetime are also sensitive to thelocal biochemical environment. As used herein, “fluorescent quantumefficiency” means the fractional number of fluorescent photons emittedfor each excitation photon absorbed or the fraction of decay eventswhich result in emission of a fluorescent photon. “Fluorescentlifetime,” as used herein, is defined as the mean survival time of theactivated fluorophore or the mean time between the absorption of anexcitation photon and emission of a fluorescent photon. Like intensity,measurement of these fluorescence characteristics is often limited towell-defined in vitro applications in the research laboratory or in flowcytometry where issues such as scattering, absorption, and changingfluorophore concentrations can be controlled or measured. Moreover,these limitations generally preclude meaningful fluorescence-basedimaging of hidden tissue heterogeneities, such as tumors or otherdiseased tissue regions, which cannot be detected by visual inspection.

With the development of techniques to interrogate tissues usingfluorescence in the near-infrared red (NIR) wavelength regime,noninvasive detection of diseased tissues located deep within normaltissues may also be possible since NIR excitation and emission light cantravel significant distances to and from the tissue-air interface. U.S.Pat. Nos. 5,213,105 to Gratton et al. and 5,353,799 to Chance are citedas further background concerning NIR interrogation. As in the case ofMRI, x-ray, CT, and ultrasound imaging modalities, there is a potentialto enhance NIR fluorescence imaging techniques with contrast agents.Typically, contrast agents for in vivo imaging have depended uponpreferential uptake into diseased tissue to provide the desired imagingenhancement by absorbing the interrogating radiation. The lightabsorbing tissue provides an enhanced spatial variation in measuredintensity of the radiation to improve image contrast. In the case of afluorescent contrast agent, the intensity of fluorescent light emittedin response to the absorption may provide this intensity variation.Generally, the larger the difference in spatial variation, asartificially imposed by a contrast agent, the more improved thereconstructed image of interior tissues. Nonetheless, the effectivenessof exogenous contrast agents depends greatly upon the selectivity of theagent for the tissue region of interest. Unfortunately, targeted andsite specific delivery of is drugs and contrast agents has historicallybeen a limiting factor in both therapeutics and diagnostic imaging.Consequently, additional mechanisms for inducing contrast that are notdependent solely upon tissue selectively of the agent would beadvantageous.

Thus, a need remains for a technique to noninvasively image multiplyscattering tissue based on one or more fluorescence characteristics.Preferably, this technique includes the implementation of exogenouscontrast agents with image-enhancing properties beyond preferentialabsorption of the interrogating radiation. The present inventionsatisfies this need and provides other advantages.

SUMMARY OF THE INVENTION

The present invention relates to spectroscopic imaging of heterogeneous,light scattering materials. Several aspects of the invention are novel,nonobvious, and provide various advantages. While the actual nature ofthe invention covered herein can only be determined with reference tothe claims appended hereto, certain features which are characteristic ofthe present invention are described briefly as follows.

One feature of the present invention is a technique for imaging aheterogeneous light scattering material. This technique includesexposing the surface of a material to light from a light source anddetecting an emission in response. A spatial variation of a fluorescencecharacteristic of the material is determined as a function of theemission with a processor. The spatial variation may be characterized bya set of values representative of the fluorescence characteristic as afunction of position. An image is generated in accordance with thespatial variation that corresponds to the heterogeneous composition ofthe material. This technique may be applied in vivo to biologic tissueusing external or endoscopic instrumentation to detect heterogeneitiesindicative of disease. The technique may include the introduction of afluorescent contrast agent into the material. The fluorescencecharacteristic detected may be fluorescence lifetime, fluorescencequantum efficiency, a fluorophore absorption coefficient, fluorescentyield (a function of fluorescent quantum efficiency and fluorophoreabsorption), or another fluorescence characteristic known to thoseskilled in the art.

Another feature includes introducing a fluorescent contrast agent into abiologic tissue. This contrast agent has a predetermined lifetime andthe tissue multiply scatters light with a mean time-of-flight betweenscattering events. The lifetime and the mean time-of-flight are within afactor of about ten of each other. The tissue is exposed to anexcitation light with a predetermined time-varying intensity and a lightemission is detected from the tissue in response to this exposure. Animage of the tissue is generated by mapping spatial variation of a levelof a fluorescence characteristic of the tissue from the light emissionin accordance with a mathematical relationship modeling multiple lightscattering behavior of the tissue.

In a further feature, the agent may be selected in accordance with apredetermined relationship between degree of image contrast and at leastone of fluorescence yield or the fluorescence lifetime. Preferably, thelifetime is in a range of about 0.1 to 10 nanoseconds (ns). A morepreferred range is 0.5 to 5 ns. A still more preferred range is about0.2 to 2 ns. A most preferred value for the lifetime is about 1 ns.

An additional feature includes evaluating ability of a number offluorescent agents to provide image contrast between different tissuetypes. This evaluation includes determining a relationship betweendegree of image contrast and at least one of fluorescence lifetime orfluorescence yield of the agent. One of the agents is selected based onthe evaluation. The selected agent is provided for introduction into abiologic tissue to enhance imaging performed in accordance with amathematical expression modeling the behavior of multiply scatteredlight traveling through the tissue.

In still another feature, a biologic tissue is exposed to a firstexcitation light and a first emission is detected from the tissue inresponse to the first excitation light. A fluorescent contrast agent isintroduced into the tissue after this detection and the tissue is thenexposed to a second excitation light. A second emission is sensed inresponse to the second excitation light. Data corresponding to the firstemission is compared with data corresponding to the second emission toevaluate contrast provided by the agent. Contrast may be determined as afunction of at least one of fluorescence lifetime, fluorescence yield,or quantum efficiency. For a frequency domain form of this evaluation,the image contrast may be evaluated in terms of phase contrast ormodulation contrast. Moreover, the wavelength of the first excitationlight may be selected to be generally the same as the wavelength of thefluorescent light emitted by the agent in response to the secondexcitation light.

Accordingly, it is one object of the present invention to map afluorescent property of a light scattering material that varies with theheterogeneous composition of the material to generate a correspondingimage.

It is another object of the present invention to provide a spectroscopictechnique for noninvasively monitoring fluorescent properties of hiddentissue volumes in a living organism and to monitor selected metabolitesof an organism in vivo.

Yet another object is to provide a technique to select and designfluorescent contrast agents who improve contrast for photon migrationbased imaging. This technique may include the selection of contrastenhancing properties that are not solely dependent upon uptake.

Further objects, features, aspects, benefits, and advantages of thepresent invention will become apparent from the drawings and descriptioncontained herein.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic illustration of a system of one embodiment of thepresent invention.

FIG. 2 is a flow chart of a process utilizing the system of FIG. 1.

FIG. 3 is a schematic representation of a tissue phantom arrangementused to demonstrate various aspects of the present invention.

FIGS. 4-7 graphically depict selected properties of equations used inthe present invention.

FIGS. 8 and 9 graphically depict convergence of simulated determinationsof the spatial variation of fluorescent yield and lifetime,respectively, utilizing one embodiment of the present invention.

FIGS. 10-14 are computer-generated gray scale images obtained fromexperimental examples 1-3 of the present invention.

FIG. 15 is a schematic illustration of a system of an alternativeembodiment of the present invention.

FIG. 16 is a schematic view of another tissue phantom arrangement of thepresent invention.

FIG. 17A is a graph of simulated measurements of phase-shift (verticalaxis) as a function of angular detector position (horizontal axis) tocompare a contrast agent with a 1 nanosecond (ns) lifetime (solid linewith open symbols) to a contrast agent with a 1 millisecond (ms)lifetime (dashed line with closed symbols); where the contrast agentsare selective to a heterogeneity and the different line styles eachcorrespond 10 millimeter (mm), 20 mm, 30 mm, 40 mm, and 50 mm positionsof the heterogeneity.

FIG. 17B is a graph of simulated measurements of modulation amplitude(vertical axis) as a function of angular detector position (horizontalaxis) to compare a contrast agent with a 1 ns lifetime (solid line withopen symbols) to a contrast agent with a 1 ms lifetime (dashed line withclosed symbols); where the contrast agents are selective to aheterogeneity and the different line styles each correspond 10 mm, 20mm, 30 mm, 40 mm, and 50 mm positions of the heterogeneity.

FIG. 18A is a graph of simulated measurements of phase contrast(vertical axis) as a function of detector position (horizontal axis) andlocation of a heterogeneity (different line styles corresponding to 10mm, 20 mm, 30 mm, 40 mm, and 50 mm positions); where the heterogeneitycontains a light-emitting contrast agent having an uptake into theheterogeneity of 100:1 and a lifetime of 1 ns.

FIG. 18B is a graph of simulated measurements of phase contrast(vertical axis) as a function of detector position (horizontal axis) andlocation of a heterogeneity (different line styles corresponding to 10mm, 20 mm, 30 mm, 40 mm, and 50 mm positions); where the heterogeneitycontains a light-emitting contrast agent having an uptake into theheterogeneity of 100:1 and a lifetime of 1 ms.

FIG. 18C is a graph of simulated measurements of modulation contrast(vertical axis) as a function of detector position (horizontal axis) andlocation of a heterogeneity (different line styles corresponding to 10mm, 20 mm, 30 mm, 40 mm, and 50 mm positions); where the heterogeneitycontains a light-emitting contrast agent having an uptake into theheterogeneity of 100:1 and a lifetime of 1 ns.

FIG. 18D is a graph of simulated measurements of modulation contrast(vertical axis) as a function of detector position (horizontal axis) andlocation of a heterogeneity (different line styles corresponding to 10mm, 20 mm, 30 mm, 40 mm, and 50 mm positions); where the heterogeneitycontains a light-emitting contrast agent having an uptake into theheterogeneity of 100:1 and a lifetime of 1 ms.

FIG. 19A is a graph of experimental measurements of phase contrast(vertical axis) of emission light as a function of detector position(horizontal axis) and heterogeneity location (different line stylescorresponding to 10 mm, 20 mm, 30 mm, and 40 mm) for a 100:1 uptake ofan ICG contrast agent into the heterogeneity.

FIG. 19B is a graph of experimental measurements of phase contrast(vertical axis) of emission light as a function of detector position(horizontal axis) and heterogeneity location (different line stylescorresponding to 10 mm, 20 mm, 30 mm, and 40 mm) for a 100:1 uptake ofan Ru(bpy)₃ ²⁺ contrast agent into the heterogeneity.

FIG. 20A is a graph comparing absorption measurements (open symbols) andfluorescent measurements (closed symbols) in terms of phased contrast(vertical axis) versus heterogeneity (object) position in centimeters(cm) (horizontal axis) for an ICG contrast agent at modulationfrequencies of 80 and 160 megahertz (MHz) (different symbol shapes).

FIG. 20B is a graph comparing absorption measurements (open symbols) andfluorescent measurements (closed symbols) in terms of modulationcontrast (vertical axis) versus heterogeneity position (horizontal axis)for an ICG contrast agent at modulation frequencies of 80 and 160megahertz (MHz) (different symbol shapes).

FIG. 20C is a graph comparing absorption measurements (open symbols) andfluorescent measurements (closed symbols) in terms of phase contrast(vertical axis) versus heterogeneity position (horizontal axis) for anDTTCI contrast agent at modulation frequencies of 80 and 160 megahertz(MHz) (different symbol shapes).

FIG. 20D is a graph comparing absorption measurements (open symbols) andfluorescent measurements (closed symbols) in terms of modulationcontrast (vertical axis) versus heterogeneity position (horizontal axis)for an DTTCI contrast agent at modulation frequencies of 80 and 160megahertz (MHz) (different symbol shapes).

FIGS. 21A-21D are computer-generated gray scale images formed fromexperimental measurements depicting spatial variation for a tissuephantom including separated ICG and DTTCI heterogeneities in terms ofmodulation phase-shift, AC modulation amplitude, average DC intensity,and modulation ratio (AC/DC), respectively.

FIGS. 22A-22D are computer-generated gray scale images depicting spatialvariation for in vivo tissue imaging of a dog treated with an ICGcontrast agent in terms of modulation phase-shift, modulation ratio(AC/DC), average DC intensity, and AC modulation amplitude,respectively.

DESCRIPTION OF PREFERRED EMBODIMENTS

For the purposes of promoting an understanding of the principles of theinvention, reference will now be made to the embodiments illustrated inthe drawings and specific language will be used to describe the same. Itwill nevertheless be understood that no limitation of the scope of theinvention is thereby intended. Any alterations and further modificationsin the described techniques, methods, systems, and devices; and anyfurther applications of the principles of the invention as describedherein are contemplated as would normally occur to one skilled in theart to which the invention relates.

FIG. 1 depicts system 110 of the present invention for fluorescentimaging of tissue 100. Tissue 100 has surface 101 and a heterogeneouscomposition as represented by regions 102, 103 underlying surface 101.Heterogeneities 102, 103 are generally not detectable by visualinspection of surface 101.

System 110 includes modulated light source 120 to supply anintensity-modulated excitation light of predetermined frequency andwavelength to tissue 100 via optic fiber 123. Preferably, source 120 isa laser diode of conventional design with a modulated output in the1-500 MHz frequency range and a monochromatic output in the 100 to 1000nanometer (nm) wavelength range. The specific wavelength is selected toexcite a designated fluorophore in tissue 100. Beam splitter 126 may beemployed to direct a small portion of the excitation signal to referencesensor 128 for processing purposes.

System 110 also includes detection subsystem 140 which has optic fibers143 to detect photons emitted from tissue 100 from a number ofcorresponding detection sites. Subsystem 140 includes one or moreemission sensors 148. Detection subsystem 140 also includes aninterference filter to obtain a selected emission wavelengthcorresponding to emission of a designated fluorophore in tissue 100. Inone embodiment, subsystem 140 includes a single sensor 148 and thesignals from fibers 143 are multiplexed. Preferably, sensors 128, 148are Photo-multiplier Tubes (PMTs) or photodiode detectors but othersensor varieties, such as image intensifiers and charge-coupled devices,are also contemplated.

Sensors 128, 148 and source 120 are operatively coupled to heterodynesubsystem 130. Subsystem 130 is configured to obtain information aboutthe phase, AC, and DC intensity of light detected with sensor 128relative to light detected with the sensor 148 using conventionalheterodyning techniques. In one embodiment, heterodyne subsystem 130includes a signal synthesizer phase-locked to the repetition rate of alaser used for source 120. For this embodiment, subsystem 130 includesan amplifier to gain modulate sensors 128, 148 at a harmonic of a laserrepetition rate (when a pulsed laser is used) or at the modulationfrequency (when a modulated laser diode is used) plus an offset toprovide the desired is heterodyning. In one variation of thisembodiment, an 80 MHz pulsed laser repetition rate is divided down to 10MHz and input to the synthesizer, and a heterodyning offset of 100 kHzis input to the amplifiers for sensors 128, 148.

Sensors 128, 148 are operatively coupled to processor 160. Processor 160includes input/control device 162, output device 164, and memory 166.Processor 160 may be an electronic circuit comprised of one or morecomponents. Similarly, processor 160 may be comprised of digitalcircuitry, analog circuitry, or both. Also, processor 160 may beprogrammable, an integrated state machine, or a hybrid combinationthereof. Preferably, input device 162 is a keyboard or input control ofa conventional variety, and output device 166 is a Cathode Ray Tube(CRT) based video display, printer, or other image display system knownto those skilled in the art. Memory 166 is preferably of the electronic(e.g. solid state), magnetic, or optical variety of the type readilyavailable for use with electronic controllers or processors.Furthermore, Memory 166 may include an optical disk memory (CD),electromagnetic hard or floppy disk media, or a combination of these.

FIG. 2 depicts one mode of operation of system 110 as process 210.Process 210 includes mapping the spatial variation of fluorescence yieldand lifetime with processor 160 and generating an image signal inaccordance with the map. Output device 164 is configured to display animage in response to the image signal. Process 210 begins by introducinga fluorescent contrast agent into tissue 100 in stage 212. This agentprovides a source of fluorescent emission for detection by subsystem240. The configuration of the modulated light source 120, heterodynesubsystem 130, and detection subsystem 140 is designed to accommodatethe excitation and emission properties of the selected fluorescentagent. In other embodiments, endogenous fluorophores may bealternatively or additionally employed and system 110 adjustedaccordingly.

In stage 214, light source 120 configured according to the selectedfluorophore excites tissue 100. In stage 216, the phase, θ_(obs), andlog of AC intensity, M_(obs), of the emission at each detection site “i”relative to the excitation light from source 120 are determined at theheterodyne (or offset) frequency. For “Di” number of detection sites,the detected or observed phase and AC intensity are indexed by “i” usingthe following notation: (θ_(obs))_(i) and (M_(obs))_(i), respectively.Processor 160 stores the relative phase and AC intensity information inmemory 166.

In stage 218, a two dimensional grid is established for an area oftissue 100 selected for imaging, and a matrix of grid points isestablished and indexed by “j”. A uniform seed value for the fluorescentyield, y_(j)=(ημ_(a) _(x→m) )j, and the fluorescent lifetime, (τ)_(j),at each grid point j is assigned. These values are an initialhomogeneous guess of the yield and lifetime values, which are modifiedin later stages. The term “η” is the quantum efficiency of thefluorophore which varies with the environment of the surrounding of thefluorophore. The term “μ_(a) _(x→m) )” is the absorption coefficient forthe fluorophore and is the product of the extinction coefficient of thefluorophore based on the natural log and the concentration of thefluorophore. As a result, the yield, y=ημ_(a) _(x→m) , is influenced bythe surrounding metabolism and the uptake of the fluorophore. The uptakeof certain known fluorophores vary with the type and condition of hosttissue, providing another fluorescence characteristic useful to detectdisease. The contrast provided by these properties is largelyindependent of fluorophore concentration. The initial estimate offluorescent yield and lifetime are stored in memory 166 by processor 160for later use.

After establishing this initial estimate of the fluorescencecharacteristics of yield, ημ_(a) _(x→m) , and lifetime, r, processingloop 220 is entered in stage 230. Preferably, the stages of processingloop 220 are executed by processor 160 via preprogrammed software,dedicated hardware, or a combination of both as appropriate. To aid inunderstanding various mathematical aspects of process 210 and loop 220,the following table of selected variables is listed:

-   -   c velocity of light in a vacuum;    -   D(r) optical diffusion coefficient;    -   Di number of detection sites;    -   f modulation frequency;    -   I identity matrix;    -   i detection site index;    -   J Jacobian matrix relating the sensitivity at each grid point,        j, to the response at each detection site;    -   j grid point index;    -   J_(j,i) individual elements of the Jacobian matrix J;    -   k source index;    -   M log of AC intensity of modulated fluorescent light position;    -   m index to multiple modulation frequencies;    -   r position (in two or three dimensions);    -   Sk number of modulated light sources;    -   S(r, ω) source term for the modulated light at position r and        frequency ω;

Greek

-   -   χ² merit function representing the least squares error;    -   φ_(x)(r,ω) complex number representing photon flux in the        Frequency domain at position r and frequency w;    -   η quantum efficiency of fluorescent probe or dye;    -   μ_(a) average absorption coefficient;    -   μ_(a) _(m) absorption coefficient of the fluorescence light by        both the nonfluorescing chromophores and fluorophore;    -   μ_(a) _(x) absorption coefficient of the excitation light by        both the nonfluorescing chromophores and fluorophore;    -   μ_(a) _(x→c) adsorption coefficient due to nonfluorescing        chromophores;    -   μ_(a) _(x→m) adsorption coefficient of excitation light by        fluorophores;    -   μ′_(s) effective scatting coefficient;    -   θ phase-shift of one modulated light wave to another;    -   τ lifetime of activated probe or dye at location r;    -   ω angular modulation frequency, given by 2πf;

Subscripts

-   -   obs observed or experimental data;    -   x excitation light; and    -   m fluorescence or emission light.

In stage 230, phase and relative AC intensity at each detection site “i”is calculated as a function of the initial estimates of yield andlifetime for each grid point j. The calculated phase and intensity arerepresented at each detection site i as (θ_(m))_(i) and (M_(m))_(i),respectively. The values for (θ_(m))_(i) and (M_(m))_(i) are determinedusing the diffusion equation approximation of the radiative transportequation. The diffusion equation approximation describes the spatial andtemporal transport of light in tissues or multiply scattering media. Acoupled frequency domain diffusion equation can be used to predict theexcitation and emission fluence rates, Φ_(x)(r, ω) and Φ_(m)(r, ω),respectively, at any location r within the selected grid of tissue 100via equations (1) and (2):

∇·[D _(x)(r)∇Φ_(x)(r,ω)]−[μ_(a) _(x) (r)+iω/c _(n) ]Φx(r,ω)+S_(x)(r,ω)=0  (1)

∇·[D _(m)(r)∇Φ_(m)(r,ω)]−[μ_(a) _(m) (r)+iω/c _(n) ]Φx(r,ω)+S_(m)(r,ω)=0  (2)

The source term for the excitation light S_(x)(r,ω) is due to thesinusoidally modulated light at an angular frequency ω=2πf where f istypically in the MHz frequency range. The first term in both of thediffusion equations (1) and (2) represents the diffusive or“random-walk” transport of multiply scattered light where D_(x,m) is theoptical diffusion coefficient of equation (3) as follows:

D _(x,m)=[3(μ_(a) _(x,m) +μ′_(s) _(x,m) )]⁻¹  (3)

and μ_(a) and μ′_(s) are the absorption and isotropic scatteringcoefficients, respectively, for tissue 100, the medium of interest.Multiple scattering of light occurs when μ′_(s)>>μ_(a); where μ_(a)indicates the ability to absorb light and μ′_(s) indicates the abilityto scatter light for a given material at a given wavelength. As usedherein, “multiply scattered light” refers to light that travels at leastfive (5) times the mean isotropic scattering length, defined as1/μ′_(s).

Because these optical properties are dependent on the wavelength oflight, the coefficients generally differ for the excitation light fromsource 120 (subscript x) and fluorescent emission detected withsubsystem 140 (subscript m). The total absorption coefficient at theexcitation wavelength, μ_(a) _(x′) is due to contributions fromnonfluorescing chromophores as well as from fluorophores responsive tothe excitation wavelength. The total absorption coefficient is given bythe sum of absorption coefficients due to nonfluorescing chromophores,μ_(a) _(x→c′) and fluorophores μ_(a) _(x→m) . Generally it may beassumed that the absorption experienced at the fluorescent wavelength isdue primarily to nonfluorescing chromophores. The velocity of light intissue is c_(n)=c/n where n is the average index of refraction. Thesource term for the fluorescent emission is dependent on the excitationlight fluence, Φ_(x)(r, ω) and is given by equation (4) as follows:

S _(m)(r,ω)=ημ_(a) _(x→m) (r)Φ_(x)(r,ω)[(1−iωτ(r))/(1+w ²τ(r)²)]  (4)

This term arises from the Fourier transform of the fluorescence decayterm in the time domain following an incident pulse of excitation lightwhere: is the fluorophore lifetime, η is the quantum efficiency, and theabsorption coefficient, μ_(a) _(x→m) , is the product of the extinctioncoefficient based on natural log and the concentration of thefluorophore in the ground state. As previously indicated, the combinedproduct, μ_(a) _(x→m) , is termed the fluorescent yield, y, and isproportional to the generated fluorescence fluence. Substitution ofequation (4) into equation (2) facilitates determination of Φ_(m) foreach grid point “j.” The solution of the diffusion equations (1) and (2)for the two-dimensional area defined by the grid points “j” may bereadily extended to three dimensions to estimate spatial variation ofone or more fluorescence characteristics in a selected volume with “r”corresponding to position in three dimensions.

Both diffusion equations (1) and (2) are linear complex ellipticequations that can be solved as boundary value problems for the complexquantities Φ_(x)(r, ω) and (r, ω). This solution employs the method offinite differences to create corresponding finite difference equations.These difference equations are utilized to obtain an approximatesolution at each grid point, j. This method of solution is described inother contexts in Fulton et al., Multigrid Method for Elliptic Problems,A Review, 114 American Meteorological Society pp. 943-59 (May 1986); andB. W. Pogue et al., Initial Assessment of a Simple System for FrequencyDomain Diffuse Optical Tomography, 40 Physics in Medicine and Biologypp. 1709-1729 (1995). One preferred method of performing this solutionis with the MUDPACK routines described in Adams, J. C., MUDPACK:Multigrid Portable Fortran Software for the Efficient Solution of LinearElliptic Partial Differential Equations, 34 App. Math Comp. p. 133(1989). For the solution of the diffusion equations, it is assumed thatΦ_(m,x)(r,ω)=0 on the surface 101 of tissue 100 which is known as thezero fluence boundary condition. It should be recognized that otherboundary conditions may be selected and the method of solution variedaccordingly.

The diffusion equations (1) and (2) may be solved for a complex numberfor ω_(m) at each grid point, j. The detected signal at the surface isproportional to the normal component of the gradient of the photonfluence. To approximate the signal at detector site “i” located onsurface 101 of tissue 100, the Φ_(m) value at an internal grid pointclosest to the site is selected which follows from the relationship thatthe normal component of the photon fluence gradient is proportional toΦ_(m) just inside surface 101. The calculated phase-lag, θ_(m), and thelog of AC intensity, M_(m), at the detection sites “Di” are calculatedfrom the imaginary and real parts of the complex Φ_(m) value withrespect to the phase and the AC intensity of source 120.

The diffusion equations (1) and (2) provide insight into the sensitivityof changing the fluorescent optical properties of tissue 100 on θ_(m)and M_(m) measured at the detector sites i. This insight results from aseries of calculations while fixing various parameters of the diffusionequations (1) and (2). These calculations assume circular tissue phantom300 with an embedded, heterogeneity 302 hidden in phantom background 303as illustrated in FIG. 3. A two-dimensional grid is established forphantom 300 and may easily be expanded to three dimensions. Under thesesimulated conditions, a large value is assigned to absorptioncoefficients for both excitation and fluorescent light at all gridpoints outside the simulated tissue phantom. The four sources S1-S4 ofFIG. 3 (Sk=4) are simulated by assigning an arbitrary complex number ata grid point near the surface closest to each source. The twentydetection sites D1-D20 of FIG. 3 (Di=20) are simulated by using thecalculated values determined from Φ_(m) at the grid point “j” closest tothe detection site. The simulated solutions to diffusion equations (1)and (2) were obtained in two dimensions for a 65×65 grid covering a 100mm diameter circular tissue phantom 300 with a circular, embeddedheterogeneity having a 30 mm diameter and located at the center of thetissue phantom 300 (this location differs slightly from theconfiguration of heterogeneity 302 of FIG. 3). The simulatedmeasurements of fluorescent phase-shift and AC intensity are reportedfor 20, equally spaced, circumferentially located detection sitesD1-D20. The modulation frequency, f, was set equal to 150 MHz. Theoptical properties of the heterogeneity and the background are shown inTable 1 as follows:

TABLE 1 μ_(s) _(x) or ημ_(a) _(x→m) τ back- μ_(a) _(x→) μ_(a) _(m) μ_(s)_(m) μ_(a) _(x→c) background ground frequency (mm⁻¹) (mm⁻¹) (mm⁻¹)(mm⁻¹) (mm⁻¹) (ns) (MHz) μ_(a) _(x→c) + 0.0 1.0 0.0 1.0 × 10⁻⁵ 1.0 150.0μ_(a) _(x→m)

In order to evaluate the influence of ημ_(a) _(x→m) , θ_(m) and M_(m)were computed at each detection site D1-D20 as the value of ημ_(a)_(x→m) in the heterogeneity increased from 10⁻⁴ mm⁻¹ to 10⁻¹ mm⁻¹ and asημ_(a) _(x→m) in the background 303 was maintained constant. Thelifetime, τ, was set equal to 1 ns for both the object and thebackground causing contrast due to differences in ημ_(a) _(x→m) . Theplots of η_(m) and M_(m) are shown in FIGS. 4 and 5 respectively for oneactive source S1. As ημ_(a) _(x→m) of heterogeneity 102 increases tohigher values, the AC intensity approaches an upper limit similar towhat is expected in dilute non-scattering solutions. FIG. 5 shows howthe fluorescent phase-shift, η_(m), decreases as the absorptioncoefficient due to to the fluorophore, μ_(a) _(x→m is decreased) 10 to100 times the background. From these simulations, M_(m) appears to bedirectly dependent upon changes in ημ_(a) _(x→m) of a simulated tissueheterogeneity 102 whereas θ_(m) is indirectly dependent on nμ_(a) _(x→m)due to changes in photon migration.

In order to evaluate the influence of τ, θ_(m), and M_(m) werecalculated at each detection site D1-D20 as the values of τ in theheterogeneity varied from 10⁻¹ ns to 10³ ns and the value of τ in thebackground was held at 1 ns. The background ημ_(a) _(x→m) was set to10⁻⁵ mm⁻¹ and ημ_(a) _(x→m) for the heterogeneity was set to 10⁻³ mm⁻¹.As shown in FIG. 6, the detected AC intensity increases as τ decreases.FIG. 7 illustrates the values of the fluorescent phase-shift at eachdetection site as the lifetime of the heterogeneity is changed from 0.1ns to 1000 ns. At a given modulation frequency (150 MHz in thiscalculation), θ_(m) first increases, reaches a maximum and thensubsequently decreases as τis increased from 0.1 ns to 1000 ns.Therefore, both θ_(m) and M_(m) at each detection site D1-D20 appear tobe directly influenced by the value of lifetime in the heterogeneity.

Referring back to FIG. 2, in stage 240, the calculated emission phaseand intensity, (θ_(m))_(i) and (M_(m))_(i), are compared to the measuredemission phase and intensity, (θ_(obs))_(i) and (M_(obs))_(i), for eachdetection site “i” to identify a difference or “error” between themeasured and calculated values. Because (ημ_(a) _(x→m) )_(j) impacts(M_(m))_(i), this comparison is posed in the form of the merit functionχμ² of equation (5) as follows:

$\begin{matrix}{x_{u}^{2} = {\left( {1/{Sk}} \right){\sum\limits_{k = 1}^{Sk}\; {\left( {1/{Di}} \right){\sum\limits_{i = 1}^{Di}\left\lbrack {\left( {\left( M_{obs} \right)_{i} - \left( M_{m} \right)_{i}} \right)/\sigma_{M}} \right\rbrack^{2}}}}}} & (5)\end{matrix}$

where σ_(M) is the typical standard deviation of noise in M_(m), takento be 0.01; Sk=number of excitation source sites indexed by k; andDi=number of detection sites indexed by i. The goal of the algorithm isto minimize χ_(μ) ² by appropriate updates of (ημ_(a) _(x→m) )j. Afteran initial update of (ημ_(a)_(x→m)j another merit function in terms of (τ)) _(j) participates in thecomparison of stage 240. This merit function, χτ², is presented asequation (6) as follows:

$\begin{matrix}{x_{\tau}^{2} = {{\left( {1/{Sk}} \right){\sum\limits_{k = 1}^{Sk}\; {\left( {1/{Di}} \right){\sum\limits_{i = 1}^{Di}\left\lbrack {\left( {\left( M_{obs} \right)_{i} - \left( M_{m} \right)_{i}} \right)/\sigma_{M}} \right\rbrack^{2}}}}} + \left\lbrack {\left( {\left( \theta_{obs} \right)_{i} - \left( \theta_{m} \right)_{i}} \right)/\sigma_{\theta}} \right\rbrack^{2}}} & (6)\end{matrix}$

where σ_(θ) is the typical standard deviation of noise in (θ_(m))_(i),taken to be 1 degree; Sk=number of excitation source sites indexed to k;and Di=number of detection sites indexed to i. Since the lifetimeinfluences both (θ_(m))_(i) and (M_(m))_(i), the phase and AC intensityare used in equation (6).

After the comparison of stage 240 is performed by calculating the meritfunctions χ_(μ) ² and χ_(τ) ² control flows to conditional 250 to testwhether the comparison of the observed values, (θ_(obs))_(i) and(M_(obs))_(i), to the calculated values (θ_(m))_(i) and (M_(m))_(i) viathe merit functions meets a selected convergence criteria. This criteriacorresponds to the degree of tolerable error in determining the yieldand lifetime values. For one embodiment, convergence is achieved whenany of the following three quantities, (i) χ², (ii) change in χ² insuccessive iterations of loop 220, or (iii) relative change in χ² insuccessive iterations of loop 220 is less than a predetermined thresholdvalue of 1.0×10⁻⁵. In other embodiments a different comparisoncalculation and associated conditional may be employed as would occur toone skilled in the art. If conditional 250 is satisfied, control flowsto stage 270 and loop 220 is exited; however, if the criteria is notsatisfied, execution of loop 220 continues in stage 260.

In stage 260, the yield, (y)_(j)=(ημ_(a) _(x→m) )_(i), and lifetime,(τ)_(j), for each grid point j is updated so that these values may reachthe minimum error corresponding to the comparison stage 240 andconditional 250 test. In order to update these values, Jacobian matricesare used which describe the sensitivity of the response at eachdetection position i to changes in (y)_(j)=(ημ_(a) _(x→m) )_(j), andlifetime, (τ_(j) at each grid point, j. Three Jacobian matrices to areemployed:

J(M,ημ_(a) _(x→m) ); J(M,τ); J(θ,τ);

where, the elements Ji,j of these Jacobian matrices are given byJi,j=[∂M_(i)/(∂(ημ_(a) _(x→m) )_(j)]; Ji,j=[∂M_(i)/∂τ_(j)],respectively. These elements may be calculated by solving the diffusion(1) and (2) four times for each grid point, j to obtain M_(m,i) andθ_(m,i) calculated with (τ)_(j) and (τ+∂τ)_(j) and with (ημ_(a) _(x→m))_(j) and (ημ_(a) _(x→m) +∂ημ_(a) _(x→m)) _(j). From least squaresminimization, the update to yield and lifetime is calculated. In onepreferred embodiment, this updating algorithm is adapted from analgorithm used to reconstruct images obtained by electrical impedancetomography like the algorithm suggested by Yorkey, et al., Comparingreconstruction Algorithms for Electrical Impedance Tomography, 34Transactions in Biomedical Engineering pp. 843-52 (1987). The JacobianMatrices are used to solve for update vectors, [ Δημ _(a) _(x→m) ] and [Δτ] to estimated yield and lifetime vectors, [ ημ _(a) _(x→m) ] and [τ], respectively. These vectors are of a dimension corresponding to thenumber of grid points. At each iteration through loop 220, the followingJacobian equations (7) and (8) are solved to determine the update forthe estimated yield and lifetime vectors:

$\begin{matrix}{{\left\lbrack {\frac{{\overset{\_}{J}\left( {M.{\eta\mu}_{a_{x\rightarrow m}}} \right)}^{T}{\overset{\_}{J}\left( {M.{\eta\mu}_{a_{x\rightarrow m}}} \right)}}{\sigma_{M}^{2}} + {\lambda_{1}\overset{\_}{I}}} \right\rbrack \left\lbrack {\overset{\_}{\Delta\eta\mu}}_{a_{x\rightarrow m}} \right\rbrack} = {\quad\left\lbrack {\frac{{\overset{\_}{J}\left( {M.{\eta\mu}_{a_{x\rightarrow m}}} \right)}^{T}}{\sigma_{M}^{2}}\left( {{\overset{\_}{M}}_{m_{obs}} - {\overset{\_}{M}}_{m}} \right)} \right\rbrack}} & (7) \\{{\left\lbrack {\frac{{\overset{\_}{J}\left( {M.\tau} \right)}^{T}{\overset{\_}{J}\left( {M.\tau} \right)}}{\sigma_{M}^{2}} + \frac{{\overset{\_}{J}\left( {\theta.\tau} \right)}^{T}{\overset{\_}{J}\left( {\theta.\tau} \right)}}{\sigma_{\theta}^{2}} + {\lambda_{2}\overset{\_}{I}}} \right\rbrack \left. \quad\left\lbrack {\quad{\quad{\quad{\quad{\quad{\overset{\_}{\Delta\tau}{\quad\quad}}}}}}} \right. \right\rbrack} = {\quad {\quad{\quad\left\lbrack {{\frac{{\overset{\_}{J}\left( {M.\tau} \right)}^{T}}{\sigma_{M}^{2}}\left( {{\overset{\_}{M}}_{m_{obs}} - {\overset{\_}{M}}_{m}} \right)} + {\frac{{\overset{\_}{J}\left( {\theta.\tau} \right)}^{T}}{\sigma_{\theta}^{2}}\left( {{\overset{\_}{\theta}}_{m_{obs}} - {\overset{\_}{\theta}}_{m}} \right)}} \right\rbrack}}}} & (8)\end{matrix}$

M _(m) _(obs) and M _(m) are the observed and calculated vectors of thelog of AC intensity at each of the i detection sites, respectively. θ_(m) _(obs) and θ _(m) are the observed and calculated vectors of thephase lag at each of the i detection sites, respectively. Due to theill-conditioned nature of the Jacobian matrices, the terms λ₁I or λ₂Iare added as part of a Marquardt minimization scheme where I is anidentity matrix. The parameters λ₁ or λ₂ are adjusted via aMaquardt-Levenberg type algorithm of the type disclosed in Press et al.,Numerical Recipes The Art of Scientific Computing, (Cambridge UniversityPress, 1992). Conventional numerical methods are employed to solve thesimultaneous linear algebraic equations resulting from the Jacobianmatrix equations (7) and (8). The Jacobian matrices are re-calculated ateach iteration through loop 220. It has been found that equations (7)and (8) provide a way to select appropriate changes to the yield andlifetime estimates; however, other numerical approaches to recursivelyiterate to acceptable estimates as would occur to one skilled in the artare also contemplated. Once the update is complete, control returns tostage 230.

If the convergence criteria is satisfied in conditional 250, thenestimation of yield and lifetime for the grid points has reached anacceptable minimum and control flows to stage 270. In stage 270 an imagesignal is generated by processor 160 from the spatial variation of theyield and/or lifetime fluorescence characteristics. This image signal issent to output device 164, which displays an image in response. Becausethe fluorescence characteristics of yield and lifetime typically varywith the biologic environment of the fluorophore, this image isgenerally indicative of tissue variation and offers the capability todetect heterogeneities 102, 103. For example, laser diodes capable ofsupplying Near infrared (NIR) light that can penetrate tissue severalcentimeters, and fluorescent contrast agents responsive to NIR light maybe used to provide a viable imaging system. In one embodiment, thissystem is adapted for use with an endoscope.

Besides yield and lifetime, the spatial variation of other fluorescencecharacteristics useful to distinguish diseased tissues may be mappedusing the diffusion equations (1) and (2). Such alternative fluorescencecharacteristics include, but are not limited to, quantum efficiency nand/or is fluorescent absorption coefficient μ_(a) _(x→m) determined asseparate properties independent of the yield product.

It should be appreciated that imaging in accordance with the presentinvention, such as process 210, includes exposing biologic tissue at thetissue-air interface to an excitation light and detecting the lightwhich has propagated to a detector located some distance away from thesource on the air-tissue interface. The time-dependent propagationcharacteristics of multiply scattered light emitted in response to thisexposure are measured. As described in connection with process 210, anintensity-modulated light source may be employed for frequency-domainmeasurements. The propagating wave of intensity-modulated light isamplitude attenuated and phase-shifted relative to the excitation lightowing to the spatial distribution of fluorescence properties. Fromexterior measurements of phase-delay and amplitude modulation, interiorfluorescence properties are determined using a mathematical relationshipthat models the multiple light scattering behavior of the tissue, suchas the diffusion equations (1) and (2). These fluorescence propertiesmay be mapped to provide a corresponding interior image of the tissue,facilitating the identification of hidden heterogeneities.

In an alternative embodiment, measurements may be made in the timedomain. For this embodiment, a pulse of light may be launched at theair-tissue interface, which is broadened during its propagation intissues due to the spatial variation of fluorescence properties withinthe tissue. The broadened pulse emitted from the air-tissue interface ismeasured. For this embodiment, the diffusion equation in the time-domainform, or such other mathematical relationship characterizing multiplyscattered light propagation through the tissue may be utilized tocalculate the fluorescence characteristics as would occur to thoseskilled in the art. These characteristics may then be mapped to generatea corresponding image in the manner described in connection with process210.

Both the frequency and time domain approaches account for the timepropagation of light through the tissue due to multiple scatteringevents. For a given photon, the travel time through a multiplescattering media increases with the number of collisions or “scatteringevents”, which corresponds to a longer scattering path. This travel timeis known as the “time-of-flight”. Typically, time-of-flight is on theorder of a fraction of a nanosecond to a few nanoseconds in biologictissue. For the usual case of many photons each traveling alongdifferent scattering paths, a mean “time-of-flight” of the photons maybe determined from the frequency or time domain measurements. Thesetime-based measurements are utilized with the corresponding mathematicalmodel to map the fluorescence characteristics.

The fluorescence characteristic map provides an image of tissue that maybe based only on intrinsic fluorophores in the tissue or enhanced byintroduction of a contrast agent that is selective to tissue volumes ofinterest. This contrast agent may absorb radiation as in the case ofcontrast agents for x-ray and CT imaging to provide a correspondingdarkening of the image regions for the tissue volumes of interest.Unfortunately, the contrast provided through selective absorption islimited. Accordingly, in another embodiment of the present invention, atechnique to select exogenous contrast agents which augment theconventional contrast mechanisms is provided. It has been discoveredthat fluorescence properties that change with the local biochemicalenvironment often provide greater contrast for reconstruction ofdiseased tissue volumes that can be afforded by absorption-basedcontrast alone. Among the properties that offer this local environmentcontrast mechanism, are fluorescence lifetime τ, i.e., the mean timebetween the absorption of an excitation photon and the emission of afluorescent photon; fluorescence quantum efficiency η, i.e., the numberof fluorescent photons emitted per excitation photon absorbed; andfluorescence quantum yield y.

It has been discovered that fluorophore contrast agents having afluorescence lifetime within an order of magnitude—or factor of ten(10)—of photon “time-of-flights” of the tissue being interrogated aresurprisingly advantageous in providing contrast for photon migrationimaging. One way of utilizing this surprising advantage is to select anagent with a fluorescence lifetime within a factor of ten (10) of themean time-of-flight predicted for the tissue to be imaged. Typically, byapplying this principle, a preferred range for the contrast agentlifetime of about 0.1 to 10 ns results. More preferably, the range forthe fluorescence lifetime of the contrast agent is within a range ofabout 0.5 to 5 ns. A still more preferred range for fluorescencelifetime of the agent is about 0.2 to about 2 ns. A most preferred valuefor the lifetime is about 1 ns.

It has also been discovered that fluorescence characteristics mayinfluence the resolution of measurements of the detected light emission.For example, in the frequency domain, it has been found that theamplitude of the intensity-modulated fluorescent light emanating from ahidden heterogeneity containing the agent generally increases withquantum yield y or quantum efficiency η. Further, as fluorescencelifetime τ within the heterogeneity increases relative to itssurroundings, the phase contrast increases. Conversely, the amplitude ofthe detected intensity-modulated light decreases with increasingfluorescence lifetime τ within the heterogeneity relative to itssurroundings. Through these discoveries, a fluorescent agent may beselected or formulated to provide a desired measurement resolution andfluorescence lifetime contrast suitable for photon migrationinterrogation of a heterogeneous arrangement of tissue. Thesediscoveries are further described in connection with Examples 4-7 at theend of this description.

Generally, as Examples 4-7 illustrate, the selection or formulation of asuitable contrast agent is performed by determining the relationshipbetween image contrast and fluorescent properties such as lifetime,yield, or quantum efficiency a function of the location of aheterogeneity selective to the given contrast agent. These relationshipsmay be evaluated for a number of different agents to select a preferredagent for a given contrast problem. For frequency domain basedevaluation, image contrast may be characterized in terms of phase shiftvariation, modulation variation, or both. Furthermore, the imagecontrast may be enhanced by measuring the response of a sample to afirst excitation light without the agent to provide a baseline (the“absence” case), and then measuring the response to a second excitationlight after introduction of the agent (the “presence” case). Datacorresponding to these two responses is compared to evaluate thecontrast capability of agent. The first excitation light wavelength maybe selected to stimulate intrinsic fluorescent response of the tissue atthe same wavelength expected to stimulate agent fluorescence.Alternatively, the first excitation light wavelength may be the same asfor the fluorescent light emitted by the agent to enhance separation ofintrinsic tissue fluorescence from fluorescence of the agent. Also,multiple comparisons may be performed using different wavelengths tobetter evaluate the influence of the contrast agent.

In another embodiment of the present invention, the photon fluenceequation and Jacobian estimation process is adapted to determine a mapof a designated fluorophore uptake concentration. For this embodiment, afirst map of chromophore adsorption coefficients μ_(a) _(x→c) andscattering coefficients μ′_(s) are determined in the absence of thedesignated fluorophore by estimating the chromophore adsorptioncoefficient μ_(a) _(x→c) and scattering coefficient μ′_(s) at each gridpoint j in place of the yield and lifetime estimates. Diffusion equation(1) for Φ_(x)(r, ω) may be used in conjunction with modified Jacobianequations (7) and (8) to create this first map. The modificationsubstitutes the chromophore adsorption and scattering coefficients inplace of the yield and after adaptation to accommodate these newcharacteristics as follows:

$\begin{matrix}{{\left\lbrack {\frac{{\overset{\_}{J}\left( {M_{x},\mu_{a_{x\rightarrow c}}} \right)}^{T}{\overset{\_}{J}\left( {M_{x},\mu_{a_{x\rightarrow c}}} \right)}}{\sigma_{M}^{2}} + \frac{{\overset{\_}{J}\left( {\theta_{x},\mu_{a_{x\rightarrow c}}} \right)}^{T}{\overset{\_}{J}\left( {\theta_{x},\mu_{a_{x\rightarrow c}}} \right)}}{\sigma_{\theta}^{2}} + {\lambda_{2}\overset{\_}{I}}} \right\rbrack\left\lbrack \overset{\_}{{\Delta\mu}_{a_{x\rightarrow c}}} \right\rbrack} = {\quad \left\lbrack {{\frac{{\overset{\_}{J}\left( {M_{x},\mu_{a_{x\rightarrow c}}} \right)}^{T}}{\sigma_{M}^{2}}\begin{pmatrix}{{\overset{\_}{M}}_{x_{obs}} -} \\{\overset{\_}{M}}_{x}\end{pmatrix}} + {\frac{{\overset{\_}{J}\left( {\theta_{x},\mu_{a_{x\rightarrow c}}} \right)}^{T}}{\sigma_{\theta}^{2}}\begin{pmatrix}{{\overset{\_}{\theta}}_{x_{obs}} -} \\{\overset{\_}{\theta}}_{x}\end{pmatrix}}} \right\rbrack}} & (9) \\{{\left\lbrack {\frac{{\overset{\_}{J}\left( {M_{x},\mu_{s}} \right)}^{T}{\overset{\_}{J}\left( {M_{x},\mu_{s}} \right)}}{\sigma_{M}^{2}} + \frac{{\overset{\_}{J}\left( {\theta_{x},\mu_{s}} \right)}^{T}{\overset{\_}{J}\left( {\theta_{x},\mu_{s}} \right)}}{\sigma_{\theta}^{2}} + {\lambda_{2}\overset{\_}{I}}} \right\rbrack\left\lbrack \overset{\_}{{\Delta\mu}_{s}} \right\rbrack} = {\quad \left\lbrack {{\frac{{\overset{\_}{J}\left( {M_{x},\mu_{s}} \right)}^{T}}{\sigma_{M}^{2}}\begin{pmatrix}{{\overset{\_}{M}}_{x_{obs}} -} \\{\overset{\_}{M}}_{x}\end{pmatrix}} + {\frac{{\overset{\_}{J}\left( {\theta_{x},\mu_{s}} \right)}^{T}}{\sigma_{\theta}^{2}}\begin{pmatrix}{{\overset{\_}{\theta}}_{x_{obs}} -} \\{\overset{\_}{\theta}}_{x}\end{pmatrix}}} \right\rbrack}} & (10)\end{matrix}$

The elements of the four Jacobian matrices employed, J(M_(x),μ_(a)_(x→c) ), J(M_(x),μ_(s)), J(θ_(x),μ_(a) _(x→c) ), and J(θ_(x),μ_(s)) aregiven

${j_{i,j} = \frac{\partial M_{xi}}{\partial\left( \mu_{a_{x\rightarrow c}} \right)_{j}}},\mspace{14mu} {j_{i,j} = \frac{\partial M_{xi}}{\partial\mu_{sj}}},{j_{i,j} = {{\frac{\partial\theta_{xi}}{\partial\left( \mu_{s} \right)_{j}}\mspace{14mu} {and}\mspace{14mu} j_{i,j}} = \frac{\partial\theta_{xi}}{\partial\left( \mu_{a_{x\rightarrow c}} \right)_{j}}}}$

respectively. Updates to the absorption and scattering map wereconducted to minimize the merit function η²:

$\begin{matrix}{\chi^{2} = {{\frac{1}{n_{s}}{\sum\limits_{k = 1}^{n_{s}}\; {\frac{1}{n_{d}}{\sum\limits_{i = 1}^{n_{d}}\left( \frac{M_{{xobs},i} - M_{x,i}}{\sigma_{M}} \right)^{2}}}}} + \left( \frac{\theta_{{xobs},i} - \theta_{x,i}}{\sigma_{\theta}} \right)^{2}}} & (11)\end{matrix}$

where n_(s)=Sk and n_(d)=Di.

After generating the first map, the designated fluorescent contrastagent is introduced, and the total adsorption coefficient μ_(a) _(x) isdetermined by substituting μ_(a) _(x) in place of μ_(a) _(x→c) inequations (9)-(11) to obtain a second map of the total adsorptioncoefficient. Noting that μ_(a) _(x) =μ_(a) _(x→m) +μ_(a) _(x→c′) andthat the uptake of the fluorescing contrast agent is directlyproportional to μ_(a) _(→m) , uptake concentration may be mapped bydetermining a difference between the adsorption coefficient variationsfor the first and second maps. This “difference map” may then be used togenerate an image corresponding to the uptake concentration.

Another alternative embodiment measures the emission responsive to eachof a number of light source modulation frequencies f. The total numberof different frequencies employed is designated Mf. To obtain thisadditional data, an iteration of loop 220 is performed for eachfrequency f indexed to m. The number of sources, Sk and detection sitesDi are indexed to k and i, respectively. This additional data may beused to enhance imaging results obtained with system 110 or to permitreduction of the number of detection sites or excitation source sites inthe evaluation. A representative merit function corresponding to thisadditional data is given in equation (12) as follows:

$\begin{matrix}{\chi_{\tau}^{2} = {{\left( {1/{Mf}} \right){\sum\limits_{m = 1}^{Mf}\; {\left( {1/{Sk}} \right){\sum\limits_{k = 1}^{Sk}{\left( {1/{Di}} \right){\sum\limits_{i = 1}^{Di}\left\lbrack {\left( {\left( M_{obs} \right)_{i} - \left( M_{m} \right)_{i}} \right)/\sigma_{M}} \right\rbrack^{2}}}}}}} + \left\lbrack {\left( {\left( \theta_{obs} \right)_{i} - \left( \theta_{m} \right)_{i}} \right)/\sigma_{\theta}} \right\rbrack^{2}}} & (12)\end{matrix}$

Besides fluorescence yield and lifetime, the multi-frequency method canbe employed to map other optical characteristics of interest. Besides asinusoidally modulated light source, the present invention may beadapted to operate with a pulsed or other time-varying excitation lightsource in alternative embodiments.

FIG. 15 depicts an optical system 410 of another embodiment of thepresent invention. This system includes modulated light source 420 withlaser driver 422, operatively coupled laser diode 424, and referencefrequency generator 426. Source 420 is configured to deliver modulatedlight to tissue phantom 400, and the emitted light from the phantom isfocused onto a gain modulated image intensifier with 50 mm lens 432through filter 433. Filter 433 may be a bandpass or low pass arrangementselected to isolate to a selected wavelength. Typically filter 433 isconfigured to pass at feast the anticipated fluorescent emissionwavelength and may additionally or alternatively be configured to passthe excitation light wavelength. Intensifier 430 includes a photocathodeface, which converts photons to electrons, a Multi-Channel Plate (MCP)which multiplies the electronic signal by avalanche multiplication, anda phosphorescent screen, which converts electrons into an optical image.Preferably, intensifier 430 is a fast intensifier, of the varietymanufactured by Litton Electronics, Inc., which enables modulation byapplying a DC bias and an RF signal from amplifier 428 between thephotocathode and the MCP. For this example, the modulation of the imagefrom intensifier 430 is phase-locked to the laser diode 424 by a 10 MHzoutput signal from synthesizer 426. By modulating the laser diode 424and the image intensifier 430 at the same frequency, a steady-stateimage results on the phosphor screen. U.S. Pat. No. 5,213,105 to Grattonet al. provides additional background concerning certain aspects of thistechnique. The image from the phosphor screen is focused throughinterference filter 433 on a Charge Coupled Device (CCD) camera 434 via150-mm macro lens 436. Camera 434 has a 512×512 array of CCD detectorsconfigured to provide a corresponding pixelated image. Camera 434 isoperatively coupled to processor 460 of a similar configuration toprocessor 160 previously described.

Following each acquired image, a phase delay between the imageintensifier 430 and the laser diode 424 is induced by stepping the phaseof the image intensifier 430 to values between 0 and 360 degrees withthe frequency synthesizer 452 under the control of processor 460. Sincethe gain modulation of image intensifier 430 and laser diode 424 occursat the same frequency, homodyning results in a steady phosphorescentimage on intensifier 430, which is dependent upon phase. Preferably,control between synthesizer 452 and processor 460 is obtained by aconventional GPIB interface. Images from the phosphorescent screen ofthe image intensifier 430 are then gathered at each phase delay. Theincremental phase delayed images are then used to generate a map ofphase-shift and intensity modulation ratio between the excitation andemitted light from phantom 400. By applying interference or appropriateoptical filters, the emission light may be selectively separated fromthe excitation light and measured. Camera 434 output may be processed byprocessor 460 using process 210.

In other embodiments, a wide area illumination source is preferred toprovide a larger, more uniform front illumination in a reflectivegeometry. This illumination approach facilitates faster imaging ofmultiple sights and a more natural physical correlation between photonmigration images and pathology. Also, a camera which has a tapered fiberoptic coupler from the image intensifier to the CCD array is envisionedto increase the efficiency of light coupling from the intensifier to theCCD array and reduce the physical size and weight of the imager.

The present invention will be further described with reference to thefollowing specific Examples 1-8. It will be understood that theseexamples are illustrative and not restrictive in nature. Examples 1-4involve the computer simulation of the process 210. Simulations of thiskind, including the simulation of tissue, are an acceptable means ofdemonstrating fluorescent spectroscopic imaging performance to thoseskilled in the art. Examples 1-3 use simulated values obtained bysolving the diffusion equations (1) and (2) for θ_(m) and M_(m) underthe conditions of table 2 as follows:

TABLE 2 Gaussian Noise Gaussian μ_(s) _(x) or τ ημ_(a) _(x→m) in log ofAC Noise μ_(a) _(x→c) μ_(a) _(m) μ_(s) _(m) (background) (background)intensity in phase Case (mm⁻¹) (mm⁻¹) (mm⁻¹) (ns) (mm⁻¹) σ_(M) σ_(θ)(degrees) 5.1 0.0 0.0 1.0 10.0 1.0 × 10⁻⁵ 0.01 0.1 5.2 1.0 × 10⁻³ 0.01.0 10.0 1.0 × 10⁻⁵ 0.01 0.1 5.3 0.0 0.0 1.0 10.0 1.0 × 10⁻⁵ 0.01 1.0

The examples simulate tissue phantom 300 of FIG. 3 having a 100 mmdiameter. Values of θ_(m) and M_(m) were computed at each of the D1-D20detection sites of FIG. 3 in response to the 4 modulated light sourcesS1-S4 located at the periphery. The excitation light modulationfrequency f was simulated at 150 MHz. Diffusion equations (1) and (2)were solved to provide 80 simulated values of θ_(m) and M_(m)corresponding to the various combinations of detection and source sites(Sk*Di=4×20=80). Gaussian noise with a standard deviation of 0.1 degrees(or a liberal 1 degree) in θ_(m) and 1% in M_(m) were superimposed onthe diffusion equation solutions. Adapted MUDPACK routines were used tosolve the diffusion equations (1) and (2) on a SunSparc10 computer.These obtained data sets were used as simulated input data to process210 for examples 1-3. The results are shown in tables 3 and 4 are asfollows:

TABLE 3 Area, object 1 Location, object 1 Area, object 2 Location,object 2 Case (mm²) (x, y), (mm, mm) (mm²) (x, y), (mm, mm) 5.1 706.0(expected) (60, 60) (expected) not applicable not applicable 742.2(obtained) (60.8, 58.5) (obtained) 5.2 706.0 (expected) (60, 60)(expected) not applicable not applicable 703.1 (obtained) (59.4, 58.3)(obtained) 5.3 314.1 (expected) (32.3, 67.7) (expected) 314.1 (expected)(67.7, 32.3) (expected) 381.0 (obtained) (34.0, 67.7) (obtained) 342.0(obtained) (65.0, 35.0) (obtained)

TABLE 4 ημ_(a) _(x→m) (object) τ (object) Case (mm⁻¹) (ns) 5.1 1.0 ×10⁻³ (expected) 1.0 (expected) 0.93 × 10⁻³ (obtained) 1.03 (obtained)5.2 1.0 × 10⁻³ (expected) 1.0 (expected) 0.8 × 10⁻³ (obtained) 0.7(obtained) (top left object): (top left object): 5.3 1.0 × 10⁻³(expected) 1.0 (expected) 2 × 10⁻³ (obtained) 4.1 (obtained) (bottomright object): (bottom right object): 2.0 × 10⁻³ (expected) 2.0(expected) 1.8 × 10⁻³ (obtained) 3.5 (obtained)

Example 1

Example 1 reconstructs fluorescent yield and lifetime with no absorptiondue to non-fluorescing chromophores. To simulate the experimental datafor this example, the fluorescent yield, (ημ_(a) _(x→m) )_(j), for thebackground and the heterogeneity 302 were chosen as 1×10⁻⁵ mm⁻¹ and1×10⁻³ mm⁻¹ respectively and the fluorescence lifetime, (τ)_(j), for thebackground and the heterogeneity 302 chosen as 10 ns and 1 nsrespectively. During the execution of loop 220, no a priori knowledge ofeither the heterogeneity 302 location or the background-fluorescenceproperties was assumed and a uniform guess of 1×10⁻⁵ mm⁻¹ and 10 ns wasgiven for the fluorescence yield, (ημ_(a) _(x→m) )j, and lifetime,(τ)_(j), respectively. Convergence was achieved in less than 50iterations of Loop 220 (computational time on a SunSparc10: 2 hours) fora two dimensional 17×17 grid. The average values of ημ_(a) _(x→m) and τin the grid points which occupy the simulated object converge within 50iterations to ημ_(a) _(x→m) =0.93×10⁻³ mm⁻¹ and τ=1.03 ns areillustrated in FIGS. 8 and 9, respectively. FIGS. 10 and 11 illustratethe reconstructed images from the mapped values of ημ_(a) _(x→m) [mm⁻¹]and τ [ns], respectively, and are representative of the expected images.The images were smoothed by interpolation in examples 1-3 to removespurious points which had unphysically high values, but were surround byvalues within a physically achievable range. These spurious values werereplaced by the average background fluorescence yield and lifetimeobtained from simulation of loop 220.

The average values of ημ_(a) _(x→m) in the grid points which occupy thesimulated background converge within 50 iterations to 9×10⁻⁵ mm⁻¹. Thevalue of the background converges to 5.4 ns. The dependence of the finalimages on the choice of the initial guess was examined by providing aninitial uniform guess of 1×10⁻⁴ mm⁻¹ and 10 ns for (nμ_(a) _(x→m) )_(j),and lifetime, (τ)_(j), respectively. This resulted in similar images tothose obtained in FIGS. 10 and 11.

The location of heterogeneity 302 was identified as consisting of allthe grid points with ημ_(a) _(x→m) higher than 35% (arbitrarily chosen)of the peak value of the ημ_(a) _(x→m) (FIG. 10). The average of thecoordinates of all the identified object grid points was the position(60.8, 58.5) which is close to position (60, 60) that was used tosimulate the experimental data. As listed in Table 3, the area of theheterogeneity based upon our arbitrary definition for identification was72 mm², close to that used to generate our simulated experimental data.

Example 2

Example 2 reconstructs fluorescent yield and lifetime with a simulatedchromophore absorption configured to mimic tissue. The same hiddenheterogeneity as well as optical parameters and simulation equipmentwere used as described in Example 1 except that a uniform backgroundchromophore absorption coefficient, μ_(a) _(x→) of 1×10⁻³ mm⁻¹ was usedto generate the simulated experimental data. While excitation lightpropagation was not employed for image reconstruction, we consideredthis optical property known to estimate the best possible performancefor inverse image reconstruction under physiological conditions. Thetwo-dimensional reconstructed spatial map of the fluorescence yield,(ημ_(a) _(x→m) )j [mm⁻¹], and lifetime, (τ)j [ns], are shown in FIGS. 12and 13, respectively. As shown in Table 3, the mean value of location ofthe object according to our criterion based on ημ_(a) _(x→m) occurred asposition (59.4, 58.3) consistent with the conditions used to simulatethe experimental data. The dimension of the heterogeneity based upon ourarbitrary definition for identification (all grid points with ημ_(a)_(x→m) higher than 35% of the maximum) were 703 mm² which is close tothat used to generate our simulated experimental data. The averagevalues of ημ_(a) _(x→m) and τ in the grid points which occupy thesimulated object converge within 50 iterations to the values of ημ_(a)_(x→m) =0.8×10⁻³ mm⁻¹ and τ=0.7 ns consistent with the values used togenerate the simulated experimental data (see Table 3). The averagevalues of ημ_(a) _(x→m) and τ in the grid points which occupy thesimulated background converge within 50 iterations to values similar tothat reported for Example 1.

Example 3

Example 3 simulated two hidden heterogeneities in the tissue phantom(not shown in FIG. 3). In this case, the same optical parameters wereused as described in example 1 except that the fluorescence yield ημ_(a)_(x→m) for the objects 1 and 2 was chosen as 1×10⁻³ mm⁻¹ and 2×10⁻³ mm⁻¹respectively and lifetime τ for the heterogeneities chosen as 1 ns and 2ns, respectively. A 33×33 grid was employed instead of a 17×17 grid. Animage corresponding to the mapping of yield is depicted in FIG. 14.

Example 4

Example 4 demonstrates the unexpected advantage of utilizing afluorescent contrast agent with a fluorescence lifetime within an orderof magnitude of the mean time-of-flight of the interrogating photons.This example compares by computational simulation, the contrast offeredby a phosphorescent agent with a lifetime of about 1 millisecond to afluorescent agent with a lifetime of about 1 nanosecond. Referring toFIG. 16, this simulation assumes a circular tissue phantom 500 with anembedded heterogeneity 502. A single source S1 is indicated anddetectors D1 through D11 are spaced about half way around the circularperiphery at generally equal intervals. For this comparison Ωτ=1 forboth the heterogeneity its surroundings. An uptake of the heterogeneityof 100 times the surroundings (background) was assumed with acorresponding absorption coefficient of fluorophores in theheterogeneity set to 0.1 cm⁻¹ versus 0.001 cm⁻¹ for the surroundings.The absorption coefficient for nonfluorescing chromophores was set to0.001 cm⁻¹ for both the heterogeneity and surroundings. The graph ofFIG. 17A plots measurements of phase shift (vertical axis) versusangular detector location about the circumference of the tissue phantom500 (horizontal axis). The lines with open symbols show phase shiftvariation of a contrast agent with a lifetime of 1 ns with the detectorposition and changes in location of a heterogeneity containing thecontrast agent (different open symbol shapes). The closed symbolscorrespond to phase shift versus detector position for a contrast agentin the heterogeneity having a lifetime of 1 ms. The graph of FIG. 17Bcompares these contrast agents in terms of Modulation (vertical axis)versus angular detector location (horizontal axis) and location of theagent-containing heterogeneity (different open symbol shapes). Theseillustrations indicate that as the lifetime increases, sensitivity ofthe contrast agent to spatial differences is reduced, and further pointto the development of fluorescent contrast agents with intrinsicrelaxation kinetics (as characterized by fluorescence lifetime) withinan order of magnitude of the photon migration times (i.e.times-of-flight) for imaging based on the behavior of multiply scatteredlight.

FIGS. 18A and 18B are calculated simulations using the same phantomtissue and parameters, comparing lifetimes of 1 ns and 1 ms,respectively, as a function of position of the detectors and location ofa heterogeneity selective to the corresponding contrast agent. Thevertical axis of FIGS. 18A and 18B represents phase contrast Δθ. Phasecontrast Δθ is the difference between the phase shift in the presence ofthe heterogeneity and the phase shift in the absence of theheterogeneity, (Δθ=θ_(presence)−θ_(absence)). FIGS. 18C and 18D arecalculated simulations using the same phantom tissue and parameters asFIGS. 18A and 18B to compare the same contrast agent lifetimes in termsof modulation contrast, ΔM (vertical axis). Modulation contrast ΔM isprovided as the ratio of the modulation ratio (AC/DC) of the detectedlight in the presence of the heterogeneity to the modulation ratio(AC/DC) of the detected light in the absence of the heterogeneity,(ΔM=M_(presence)/M_(absence)). For all of FIGS. 18A-18D, the horizontalaxis corresponds to the detector number and the different line stylescorrespond to different positions of the contrast agent-bearingheterogeneity.

Example 5

The conclusions of the simulation of Example 4 have further beenempirically demonstrated by the experimentation of Example 5. Theexperimental equipment set-up for Example 5 is comparable to system 110.A tissue phantom is prepared by filling a cylindrical Plexiglascontainer having a 20 cm diameter and a 30.5 cm height with a 0.5%Intralipid solution (supplied by Kabi Parmacia, Clayton, N.C.). Aheterogeneity is provided by placing a cylindrical glass container witha 9 mm inner diameter in the Plexiglas container and filling the glasscylinder with the intralipid solution and a contrast agent. The positionof the heterogeneity within the Plexiglas container is adjusted with anx-y translation stage model number PMC200-P supplied by Newport ofIrvine, Calif.

Example 5 experimentally confirms the phase contrast simulated inExample 4 by comparing phase contrast Δθ with a Ru(bpy)₃ ²⁺phosphorescent contrast agent in the inner glass container (FIG. 19B) toa fluorescent contrast agent, Indocyanine Green (ICG) (supplied by ACROSOrganics, Fairlawn, N.J.), in the inner glass container (FIG. 19A). Thecontrast agents where added to the intralipid solution in the innerglass container (the “heterogeneity”) to simulate a 100:1 uptake ratio.Ru(bpy)₃ ²⁺ has a lifetime on the order of microseconds. ICG has alifetime of about 0.58 ns. Notably, by comparing FIGS. 19A and 19B, thephase contrast (vertical axis) provided by a fluorescent agent with itssmaller lifetime, is substantially greater than the phase contrastprovided by the longer-lived phosphorescent agent Ru(bpy)₃ ²⁺ as afunction of detector number (horizontal axis) and heterogeneity location(different line styles).

Example 6

The experimental equipment set-up for Example 6 is comparable to Example5, except a single source and a single detection point were utilized.The source and detector were placed along the circumference a fewdegrees apart and the inner container was generally positioned along themidline defined between the source and detector. The x-y stage was usedto adjust the position of the inner container along this midline toobserve corresponding changes in phase shift θ and amplitude.

In Example 6, the response of two different fluorescent contrast agentsICG and 3-3′-Diethylthiatricarbocyanine Iodide (designated “DTTCI”herein and supplied by ACROS Organics, Fairlawn, N.J.) to anintensity-modulated excitation light having a wavelength of about 780 nmwas detected. The excitation light was modulated at 80 MHz and 160 MHzin different trials corresponding to lines with different symbol shapes.ICG is an agent approved for hepatic and retinal diagnostic testing witha measured lifetime of about 0.58 nanoseconds and DTTCI is a commonlaser dye with lifetime of about 1.18 nanosecond.

The phase shift and modulation ratio of the tissue phantom in theabsence of the heterogeneity was measured to provide the “absence” caseneeded to calculate phase contrast Δθ and modulation contrast ΔM. Next,an ICG contrast agent was prepared by adding about a 2.0 μmole ICGconcentration to a 0.5% intralipid solution in the inner container. TheICG sample was then exposed to excitation light from the source and theresponse detected. This detection included measurement of absorption ata wavelength of 780 nm and fluorescence at 830 nm. The resulting phasecontrast Δθ at the absorption wavelength (open symbols) and forfluorescence wavelength (closed symbols) for the ICG sample was plottedon the vertical axis of the graph provided in FIG. 20A with thehorizontal axis showing the relative position of the heterogeneity(“object”) in centimeters as it is moved toward the detector and sourcealong the midline. The resulting modulation contrast ΔM at theabsorption wavelength (open symbols) and at fluorescence wavelength(closed symbols) for the ICG sample was plotted on the vertical axis ofthe graph provided by FIG. 20B with the horizontal axis showing therelative position of the object in centimeters as it is moved toward thedetector and source along the midline.

After ICG sample was tested, a 4.2 μmole concentration of the DTTCIcontrast agent was added to the 0.5% intralipid solution in the innercontainer to provide a DTTCI sample. The different concentration of theICG and DTTCI contrast agents were selected to provide a fluorescentcross-section that is generally the same for both the ICG and DTTCIsamples. The resulting phase contrast Δθ at the absorption wavelength(open symbols) and at the fluorescence wavelength (closed symbols) forthe DTTCI sample is plotted on the vertical axis of the graph providedin FIG. 20C with the horizontal axis showing the relative position ofthe object in centimeters as it is moved toward the detector and sourcealong the midline. The resulting modulation contrast ΔM at theabsorption wavelength (open symbols) and for fluorescence wavelength(closed symbols) for the DTTCI sample is plotted on the vertical axis ofthe graph provided in FIG. 20D with the horizontal axis showing therelative position of the object in centimeters as it is moved toward thedetector and source along the midline.

For both samples, the fluorescence decay process is single exponential,showing one lifetime, but the analysis and approach can be extended todyes and contrast agents with more than one lifetime. Upon comparing thefluorescent phase and amplitude modulation generated by the twofluorescent contrast agents, the impact of fluorescence lifetime t overabsorption may readily be observed. Indeed, it has been found thatsubstantial contrast is present when the uptake is only 10:1 over thesurroundings or background.

Example 7

For Example 7, a phantom tissue is prepared by placing atissue-mimicking Intralipid solution in a Plexiglas container. Theexcitation light source transilluminates the tissue phantom from therear along a straight-line distance of about 8 centimeters. An imageintensifier/CCD detection arrangement was utilized to detect theresponse. The experimental set-up for Example 7 was comparable to system410 illustrated in FIG. 15.

Embedded within the middle of the Plexiglas container tissue phantomwere two micromolar intralipid solutions of 0.5 ml in separatecontainers each having a different fluorescent contrast agent. Onevessel included an ICG contrast agent and the other vessel included aDTTCI contrast agent. Measurements of the fluorescent phase-shift, ACamplitude, DC intensity, and modulation (AC/DC) were conducted acrossthe front of the phantom tissue in response to a 100 MHz modulatedexcitation light at 780 nm. FIGS. 21A-21D are two-dimensional imagesdepicting the spatial variation of the phase-shift, AC amplitude, DCintensity, and modulation measurements; respectively, in terms of acorresponding gray scale. These images confirm the variation in contrastwith differences in fluorescence lifetime and the parameter beingmeasured.

Example 8

Example 8 is a live tissue study of mammary tissue from a dog, SugarLimburg, which was a miniature poodle (age 10 years and weight 12.5lbs.). An in vivo image of the right fifth mammary glad was taken afteran in vivo injection with 1.3 cc of a 5% concentration of ICGfluorescent contrast agent. Interrogation was performed with anexperimental set-up comparable to Example 7, with an excitation lightwavelength of 789 nm and detection at a 830 nm wavelength. Themodulation frequency was 100 MHz.

A frozen section of the right fifth mammary revealed two dark spotsapproximately 1 cm deep from the tissue surface which werehistologically classified as reactive regional inguinal lymph nodes withno evidence of metastatic spread. The remaining tissue was classified aslobular hyperplasia with no evidence of tumor. FIGS. 22A-22D are2-dimensional images depicting spatial variation in terms of in vivomeasurement from the emission light for modulation phase, modulationratio, average intensity, and modulation amplitude, respectively,relative to corresponding gray scales. The white line in the image ofFIGS. 22A-22D is the air-tissue boundary. The phase shift in the tissueis small due to the small amount of mammary tissue present. Also, themodulation ratio contains a large amount of background noise. However,the two light spots at the bottom of both the average intensity and themodulation amplitude are believed to correspond to an increased uptakeof ICG inside the enlarged lymphatic tissue.

All publications and patent applications cited in this specification areherein incorporated by reference as if each individual publication orpatent application were specifically and individually indicated to beincorporated by reference; including U.S. patent application Ser. Nos.60/039,318 filed 7 Feb. 1997 and 08/702,060 filed 23 Aug. 1996. Whilethe invention has been illustrated and described in detail in thedrawings and foregoing description, the same is to be considered asillustrative and not restrictive in character, it being understood thatonly the preferred embodiments have been shown and that allmodifications that come within the spirit of the invention are desiredto be protected.

1.-33. (canceled)
 34. A method, comprising: evaluating ability of anumber of fluorescent agents to provide image contrast between differenttissue types, said evaluating including determining a relationshipbetween degree of image contrast and at least one of fluorescencelifetime or fluorescence yield of the agent; selecting one of the agentsbased on said evaluating; and providing the selected one of the agentsfor introduction into a biologic tissue to enhance imaging performed inaccordance with a mathematical expression modeling the behavior ofmultiply scattered light traveling through the tissue.
 35. The method ofclaim 34, wherein the at least one is fluorescence lifetime.
 36. Themethod of claim 34, wherein the mathematical expression corresponds to adiffusion equation approximation of multiply scattered light.
 37. Themethod of claim 36, further comprising applying the diffusion equationapproximation in a frequency domain form.
 38. The method of claim 34,further comprising generating an image of the tissue by mapping spatialvariation of a level of a fluorescence characteristic of the tissue. 39.The method of claim 34, wherein the mathematical expression is in afrequency domain form and the image contrast is provided in terms of atleast one of phase shift contrast or modulation contrast.
 40. A method,comprising: exposing a biologic tissue to a first excitation light;detecting a first emission from the tissue in response to the firstexcitation light; introducing a fluorescent contrast agent into thetissue after said detecting; exposing the tissue after said introducingto a second excitation light; sensing a second emission in response tothe second excitation light; comparing data corresponding to the firstemission with data corresponding to the second emission to evaluatecontrast provided by the agent as a function of at least one offluorescence lifetime, fluorescence yield, or quantum efficiency. 41.The method of claim 40, wherein the at least one is fluorescencelifetime.
 42. The method of claim 41, wherein the fluorescence lifetimeis in a range of about 0.1 to 10 nanoseconds.
 43. The method of claim41, wherein the fluorescence lifetime is in a range of about 0.5 to 5nanoseconds.
 44. The method of claim 41, wherein the fluorescencelifetime is in a range of about 0.2 to 2 nanoseconds.
 45. The method ofclaim 40, further comprising evaluating the first and second emissionswith a mathematical expression modeling the behavior of multiplyscattered light traveling through the tissue.
 46. The method of claim45, wherein the mathematical expression corresponds to a diffusionequation approximation of multiply scattered light.
 47. The method ofclaim 40, further comprising generating an image of the tissue bymapping spatial variation of a level of a fluorescence characteristic ofthe tissue.
 48. The method of claim 47, wherein the fluorescencecharacteristic is at least one of fluorescence lifetime, fluorescenceyield, or fluorescence quantum efficiency.
 49. The method of claim 47,wherein said generating includes determining a modulation amplitudechange and a phase change of the light emission relative to theexcitation light.
 50. The method of claim 49, wherein the fluorescencecharacteristic corresponds to the fluorescence lifetime.
 51. The methodof claim 40, wherein wavelength of the first excitation light isgenerally the same as wavelength of fluorescent light emitted by theagent in response to the second excitation light.